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This note reanalyzes Cox's idealized example of testing with data splittingusing e-values (Shafer's betting scores). Cox's exciting finding was that themethod of data splitting, while allowing flexible data analysis, achieves quitehigh efficiencies, of about 80%. The most serious objection to the method wasthat it involves splitting data at random, and so different people analyzingthe same data may get very different answers. Using e-values instead ofp-values remedies this disadvantage.

A note on data splitting with e-values: online appendix to my comment on Glenn Shafer's "Testing by betting"